Category: automated mapping

BioBase Paper Published: Accuracy and Precision of Low-Cost Echosounder and Automated Data Processing Software for Habitat Mapping in a Large River

We are grateful to the aquatic research community who continue to verify and validate Consumer Sonar Technologies (Lowrance) and BioBase automated mapping platform to produce scientifically valid outputs that benefit aquatic conservation.  We are excited to see the recent publication of research out of the University of New Brunswick that evaluated the accuracy and precision of Lowrance and BioBase’s EcoSound depth and vegetation outputs.  The research is published in the open access journal Diversity and can be downloaded here. Below is the abstract

Abstract
The development of consumer hydroacoustic systems continues to advance, enabling the use of low-cost methods for professional mapping purposes. Information describing habitat characteristics produced with a combination of low-cost commercial echosounder (Lowrance HDS) and a cloud-based automated data processing tool (BioBase EcoSound) was tested. The combination frequently underestimated water depth, with a mean absolute error of 0.17 ± 0.13 m (avg ± 1SD). The average EcoSound bottom hardness value was high (0.37–0.5) for all the substrate types found in the study area and could not be used to differentiate between the substrate size classes that varied from silt to bedrock. Overall, the bottom hardness value is not informative in an alluvial river bed setting where the majority of the substrate is composed of hard sands, gravels, and stones. EcoSound separated vegetation presence/absence with 85–100% accuracy and assigned vegetation height (EcoSound biovolume) correctly in 55% of instances but often overestimated it in other instances. It was most accurate when the vegetation canopy was ≤25% or >75% of the water column. Overall, as a low-cost, easy-to-use application EcoSound offers rapid data collection and allows users with no specialized skill requirements to make more detailed bathymetry and vegetation maps than those typically available for many rivers, lakes, and estuaries.

EcoSound vs Manual Measures Vegetation Helminen et al 2019

Guest Blog: BioBase and Arctic charr habitat in Windermere, U.K.

By Dr. Ian J. Winfield and Joey van Rijn

The Arctic charr (Salvelinus alpinus) is well appreciated as an important fisheries species in many northern areas of the world.  In addition, it is equally important to evolutionary biologists because of this species’ frequent development of ‘morphs’ or ‘types’ and their bearing on our understanding of mechanisms of speciation (Figure 1).  In the U.K., this fascinating fish is also recognised as having great nature conservation value.

Figure 1.  A female (top) and male (bottom) Arctic charr from Windermere, U.K.  Photo courtesy of the Center for Ecology and Hydrology)

Windermere is England’s largest lake and has been at the forefront of several areas of Arctic charr research for many decades, with the notable exception of studies of their spawning grounds (Figure 2).  Despite their long appreciated significance for the coexistence of autumn- and spring-spawning Arctic charr types, local spawning grounds have not been studied in any detail since their original brief description in the 1960s.  At that time, laborious and spatially-limited direct observations by divers showed that spawning requires the availability of gravel or other hard bottom habitat.  New information on these critical areas is needed by ecologists and evolutionary biologists and, more urgently, by fisheries and conservation organisations responsible for the management of Windermere.

Figure 2.  Breathtaking view of Windermere’s north basin; home to several spawning populations of Arctic charr.  Photo courtesy of Dr. Ian Winfield.

We are currently using the newly developed bottom hardness capability of ciBioBase to survey and characterise the spawning grounds of Arctic charr in Windermere.  Limited underwater video is being used for ground-truthing, but the combination of a Lowrance™ HDS-5 sounder with ciBioBase is allowing us to investigate the known spawning grounds with unprecedented speed (Figure 3).  For the first time, we have been able to document in detail the bathymetry and bottom features of a long-monitored (for spawning fish) spawning ground just north of the island of North Thompson Holme in the lake’s north basin.  ciBioBase is also enabling us to examine other known spawning grounds in Windermere and to expand our coverage to other potential areas previously unstudied.

Figure 3. An example ciBioBase output of bottom composition on and around the Arctic charr spawning ground of North Thompson Holme in the north basin of Windermere

The rapidity of the field component of hydroacoustic surveys is well known.  ciBioBase now offers us a similarly fast method of hydroacoustic data analysis for key environmental characteristics in relation to the spawning of Arctic charr.  This new approach helps us to dramatically increase our return on investment and also allows us to review results within hours of coming off the water, leading in some cases to us adapting our field plans on the basis of initial results.

Dr. Ian J Winfield is a Freshwater Ecologist at the Centre for Ecology & Hydrology in Lancaster, U.K.  He has over 30 years of research experience in fish and fisheries ecology, hydroacoustics, and lake ecosystem assessment and management.  Dr. Winfield sits on several regional, national and international advisory boards and is the current President of the Fisheries Society of the British Isles (FSBI).

Joey van Rijn is an undergraduate student currently following a BSc. degree course in Applied Biology at the University of Applied sciences, HAS Den Bosch, in the Netherlands. He is experienced in ecological and particularly phenological research including work on temperature-induced differences between urban and rural areas in the timing of blossoming and leaf unfolding in shrubs.  He has also been involved with the development of fish ways for standing waters in the Netherlands. Joey is currently undertaking a research internship at the Centre for Ecology & Hydrology in Lancaster, U.K., where his research mainly focuses on using hydroacoustics to investigate Arctic charr spawning grounds in Windermere.

Bathymetry Mapping with ciBioBase!

At Contour Innovations, we often preach the importance of aquatic plant mapping and monitoring, but of equal importance and capability is ciBioBase bathymetric mapping features.  ciBioBase comes with many features that automate the tedious, mundane, yet highly technical GIS processes associated with creating a bathymetric map.  Water resource and lake managers and researchers should be spending their time and talents focusing on thorny management problems, not compiling and managing volumes of data and trying to map them in GIS.  The science of acoustic bottom detection and GIS mapping has been extensively tested, verified, and proven with standard methods.  We automate this.

Because ciBioBase maps only areas you cover up to a 25-m buffer outside of your track, you are assured that maps do not include extrapolated data.  40-m spacing of transects with a criss-cross design assures you that you will get complete coverage and smooth contours (Figure 1). 

Figure 1. Transect coverage showing a “criss-cross” design to assure a high quality bathymetric map.

The Trip Replay feature in ciBioBase further allows you to see disruptions in the contours (Figure 2).  As in the case with Figure 2, there was a temporary disruption in the transducer signal, thus giving an erroneous depth (Figure 2 and 3).  In ciBioBase, these erroneous depths can be edited out; thus creating a smoother, more accurate bathymetric map and associated statistics.

Figure 2. Desktop verification of bathymetric outputs with ciBioBase’s Trip Replay feature.
Figure 3. Areas of disrupted signal can be deleted and the trip reprocessed for a more accurate and smooth bathymetric map.

Other times, these little “donuts” occur because depths temporarily enter a different contour level (e.g., 3ft contours with series depths = 5.99, 6.0, 5.99, 5.98, etc).  Although the 6.0 depth is likely legit, it may be more aesthetically pleasing to remove the 6.0 depth to prevent the creation of a 6ft donut hole.

Once you are happy with the output with individual trips, you can merge them in ciBioBase to create a uniform output (Figure 4).

Figure 4.  Merging function in ciBioBase that allows users to merge individual files or trips into a single, uniform map.

Tying Bathymetry to a Benchmark Elevation
When mapping bathymetry, it may be important to tie the water level to a benchmark water level elevation.  In our Minnesota Lake example, we went to the Minnesota Department of Natural Resource’s Lakefinder website and found important water level information (Figure 5).  On 6/5/2012, we surveyed McCarron’s Lake in Ramsey County, MN.  On 6/7/2012, the elevation-corrected water level reported by citizen volunteers was  840.84 ft above sea level.  The Ordinary High Water Level  (OHW) benchmark for McCarron’s is 842.21 ft (Figure 5).  Using the Data Offset feature in ciBioBase (Figure 6), we can simply add 1.37 ft (elevation correction) plus 1 ft (transducer correction) to get a bathymetric map that is corrected to the OHW (Figure 7).  This eliminates water level as a confounding variable with repeated bathymetric surveys on the same waterbody.  The final products are high resolution, blue-scale imagery as seen in Figure 7 (up to 1-ft contours) or the actual point and grid data that can be imported into any third party GIS or statistical software (Figure 8).

Figure 5. Water level information for McCarron’s Lake in Ramsey County, Minnesota USA.
Figure 6. Data Offset feature in ciBioBase that allows users to correct their bathymetric data to a benchmark water level and transducer depth.
Figure 7. Bathymetric imagery with resolution (both bottom and pixel) that can be controlled by the user.
Figure 8. Export point data along your traveled path or the kriging interpolated grid for use in third party GIS or statistical software.

Life is good in the cloud…

Because of the centralized, cloud-based platform of ciBioBase, we see trip uploads into the system from all types of lakes, ponds, and reservoirs throughout the country and even abroad; so our acoustic and geostatistic algorithms have seen it all!

See for yourself in our demo account at ciBioBase.com.  In the login page, enter demo@cibiobase.com and “demo” for the password.  Operators are standing by to answer any questions you may have!

What to do with all this Lake Habitat Data!?

Fifteen data points per second, four hours on Lake X today, several more tomorrow.  Lake Y and Z to follow.  Repeat next year and the year after.  Since no one has to process the data, it can be collected during non-dedicated mapping time by hitting record on your Lowrance HDS each time  your on the water.  Simple math tells you that this is going to lead to A LOT of data.  What are you going to do with it all?

This “problem” is new to biologists and lake management practitioners in the 21st Century.  Decision making in a data “poor” environment has been much more common and indeed is still a real problem.  The “problem” of too much data, really isn’t a problem at all.  Modern computing technology can return only information that is important to you and archive the rest for safe keeping.

With regards to aquatic plant assessment and monitoring in lakes, never before have we been able to rapidly collect and interpret information about how much plants are growing and where.   So, we spend three hours going back and forth on our favorite 230 acre, upload our data to ciBioBase and get a pretty map and some statistics on the density of the vegetation (Figure 1).  So what?  What does it mean?

Figure 1.Example automated summary report from ciBioBase.

Well, admittedly it is difficult to judge whether 78% of the lake being covered with vegetation (PAC) is normal.  What is normal?  This exemplifies the importance of collecting baseline information to judge whether changes from time A or B are significant.

The invasive aquatic plant, Eurasian watermilfoil has a tendency to grow to the surface of lakes, displace native plant species, and impede navigation.  The extent of surface growth and overall cover of Eurasian watermilfoil and other invasive plant species are typically the conditions that lake managers and citizens want to reduce.  ciBioBase provides a rapid and objective way to monitor how cover and surface growth of vegetation is changing as the lake is affected by various stressors and our responses to them (e.g., herbicide treatments).  For instance, often a water resource agency or citizen group will state objectives in a lake management plan something to the effect of “Objective 1: reduce the abundance of Eurasian watermilfoil by 80%.”  What should be asked next is 80% of what? What is our yardstick?  We can’t expect to be successful at water and fisheries resource conservation without clearly defining management targets and evaluating whether we’re getting there.

Furthermore, there is a tight link between water quality and aquatic plant growth.  Clear lakes with all native plant species often have high cover of vegetation, but relatively little surface-growing vegetation (except near shore or in shallow bays).  As more nutrients run into the lake from lawns and parking lots, aquatic plants initially increase in abundance and grow closer to the surface to get sunlight from the clouding water.  If we continue to mow our lawns down to the lake edge, over fertilize, and route water from parking lots and roofs into our lakes unabated, then aquatic plants crash because the water is too turbid to support plant growth.  Next thing you know, largemouth bass, bluegill, and northern pike disappear and you find your lake on the EPA’s Impaired Water’s List and now you need to spend million’s to clean it up.  ciBioBase can be used to prevent you from getting to that point.

One precise way of doing so is to monitor the maximum depth that vegetation grows in your lake.  There is a tight link between water clarity and the depth that plants grow in lakes (Figure 2).  The extent of plant growth integrates the short-term dynamic nature of water clarity and gives a measure of the overall water clarity conditions for the year.  The conventional water clarity monitoring routine involves citizens and lake managers taking a dozen trips a season to the middle of the lake to drop a Secchi disk down and measure the distance where the disk disappears from sight.  With one 3-hr mid-summer ciBioBase survey, you can get a measure of water clarity conditions for the entire season.  This depth should remain relatively consistent from year to year in stable watershed and lake conditions.  A change of two feet over the course of a couple of years should raise a flag that conditions in the lake may be changing and initiate some initial investigation into possible causes.



Figure 2. Relationship between the maximum depth of vegetation growth as a function of water clarity from 33 Minnesota lakes where lakes were mapped with sonar and water clarity data was collected with a Secchi disk.

To bring this discussion full circle, we should ask: how do we know the change in point A or B is due to a real change in lake conditions and not an artifact of our sampling?  This question plagued the 20th Century Lake Manager to the point of gridlock.  In the 21st century, we can overwhelm the question with data to get almost a census of the current conditions rather than a small statistical sample fraught with error.  Lake Managers don’t have to physically wade through all this data to find the answer.  High-powered computers and processing algorithms can do the heavy lifting, the lake manager or concerned citizen can focus on implementing practices that will result in clean water and healthy lake habitats.

Assessing Fish Habitat in Rivers

BioBase is not just a lake vegetation mapping tool, it also can help Fisheries managers and researchers assess, monitor, and simulate fish habitat conditions in large rivers.  We demonstrated this application on a trip to the Mississippi River Pool 2 in St. Paul, MN on 4/27/2012.  Just downstream of the Lock and Dam, we used a Lowrance HDS sounder and the automated processing of BioBase to map the bathymetry of a pool where a range of fish species often congregate (Figure 1).

Figure 1.  Bottom mapping with a Lowrance HDS-5 on Pool 2 of the Mississippi R. just downstream of the Lock and Dam on 4/27/2012.

 

The raw pool elevation on 4/27/2012 was 4.27 feet; still within the range of moderate drought according to the US Drought Monitor but 1.7 feet higher than the most recent low on 12/10/2011. Coincidentally, these drought levels follow historic flood levels just one year earlier (Figure 2). To demonstrate BioBase’s utility as a fish habitat assessment tool, we compared sizes and volumes of our mapped pool under the hydrologic conditions experienced on Pool 2 during the last year.

Figure 2. Hydrograph for the Mississippi River at St. Paul, MN (DNR ID# 20088002; USGS ID# 05331000; Data and figure courtesy of the MN DNR).


On 4/27/2012, we mapped and analyzed a 15-ft pool using the ciBioBase polygon creation tool and determined that the max depth was 17 ft, surface area was 317 m2 and the volume was 1508 m3 (Figure 3).

Figure 3.  Diagnostics of a pool of interest using BioBase’s polygon tool.

In order to reconstruct changes to this pool under the recent low flow on December 10th 2011, we used the Z-depth Offset feature iniBioBase to drop the elevation down 1.7 feet.  In Figure 4, you can see the striking difference this reduction has on the size of this pool and consequently the amount of available fish habitat.  The area on December 10th 2011 was estimated to be 3.1 m2 and volume was 9.4 m3; 100 times smaller in size and 161 times smaller in volume than on 4/27/2012. If we increase the offset by the peak flood elevation on March 30th 2011, the 15-foot hole becomes a 30-foot hole (Figure 5).

 

Figure 4. Polygon overlay in BioBase demonstrating the difference in size and volume of a 15-ft deep hole between the yearly low elevation on 12/10/2011 (pink) and during data collection on 4/27/12 (green).

 

Figure 5. Polygon overlay of drought elevations in 2012 (green and pink) overlain onto simulated peak flood bathymetry on 3/30/2011.
This demonstrates one potential application of BioBase for fish habitat studies in large rivers.  We presented three striking contrasts in fish habitat conditions within one year’s time with data that took 20 minutes to collect and an hour to analyze in BioBase. Different hydrological scenarios can be modeled in BioBase and thus could be used in predictive fisheries habitat models or to reconstruct habitat conditions over some period of time.
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